ArticleNature ecology & evolution2021
A theoretical analysis of tumour containment.
Article in Nature ecology & evolution, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.
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Who cites it
52 citing papers in PubMed, 96 citations in OpenAlex.
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- Single-threshold-guided adaptive cancer therapy with partial-cycle treatment: A mechanistic and reinforcement learning analysis.PLoS computational biology · 2026Article
- Evolutionary Double-Bind Treatment Using Radiation Therapy and Natural Killer Cell-Based Immunotherapy in Prostate Cancer.International journal of radiation oncology, biology, physics · 2026Article
- Growth rate-driven modelling suggests that phenotypic adaptation drives drug resistance in BRAFV600E-mutant melanoma.Communications biology · 2026Article
- Optimal control theory as a method for designing multidrug adaptive therapy regimens.NPJ systems biology and applications · 2026Article
- Selective sweep probabilities in spatially expanding populations.Nature communications · 2026Article
- Can evolutionary therapy be applied in non-small cell lung cancer?Scientific reports · 2026Article
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- Precision oncology in gynecologic cancers: molecular taxonomy, biomarker-guided therapeutics, and the challenge of therapeutic resistance.Frontiers in oncology · 2026Review
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- Adaptive therapy and its challenges.Evolution, medicine, and public health · 2026Article
- Employing nullclines to balance treatment efficacy and neurotoxicity for sustained tumor control.Mathematical biosciences · 2025Article
- Cancer model with moving extinction threshold reproduces real cancer data.Journal of the Royal Society, Interface · 2025Article
- Deriving Optimal Treatment Timing for Adaptive Therapy: Matching the Model to the Tumor Dynamics.Bulletin of mathematical biology · 2025Article
- Extrachromosomal DNA: shaping the evolutionary dynamics of cancer.Trends in cancer · 2025Review
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- Quantitative measurement of phenotype dynamics during cancer drug resistance evolution using genetic barcoding.Nature communications · 2025Article
- Bringing evolutionary cancer therapy to the clinic: a systems approach.NPJ systems biology and applications · 2025Review
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 3 countries.
Funding
Abstract
Recent studies have shown that a strategy aiming for containment, not elimination, can control tumour burden more effectively in vitro, in mouse models and in the clinic. These outcomes are consistent with the hypothesis that emergence of resistance to cancer therapy may be prevented or delayed by exploiting competitive ecological interactions between drug-sensitive and drug-resistant tumour cell subpopulations. However, although various mathematical and computational models have been proposed to explain the superiority of particular containment strategies, this evolutionary approach to cancer therapy lacks a rigorous theoretical foundation. Here we combine extensive mathematical analysis and numerical simulations to establish general conditions under which a containment strategy is expected to control tumour burden more effectively than applying the maximum tolerated dose. We show that containment may substantially outperform more aggressive treatment strategies even if resistance incurs no cellular fitness cost. We further provide formulas for predicting the clinical benefits attributable to containment strategies in a wide range of scenarios and compare the outcomes of theoretically optimal treatments with those of more practical protocols. Our results strengthen the rationale for clinical trials of evolutionarily informed cancer therapy, while also clarifying conditions under which containment might fail to outperform standard of care.
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